1.6 KiB
1.6 KiB
GPT-Pretrain
Usage
Make it simple
python lit_train.py --model_name gpt2 --use_tril_attention_mask
python lit_export.py --version 0
python generate.py --model_name_or_path exports/version_0 --tokenizer_name_or_path gpt2
📝 Note: Training with a "--use_tril_attention_mask" is recommended. However, huggingface model implementions might not support 2D attention mask. You may write a custom model to support 2D attention mask, just like what I did in custom_models/gpt2.
Train on multiple GPUs
python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy fsdp # default and recommended
python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy deepspeed
python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy ddp
Reduce CUDA memory cost
- half precision
python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16python lit_train.py --model_name gpt2 --use_tril_attention_mask --fp16 - smaller batch size & accumulate grad batches
python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \ --train_batch_size 2 --val_batch_size 4 --accumulate_grad_batches 128 - cpu_offload
python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \ --strategy fsdp_cpu_offloadpython lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \ --strategy deepspeed_stage_3_offload